Deep Learning: Modular in Theory, Inflexible in Practice with Diogo Almeida

The podcast you’re about to hear is one of a handful of interviews I recorded live from the O'Reilly AI and Strata conferences in New York City. This time, I interview Diogo Almeida, senior data scientist at healthcare startup Enlitic. Diogo’s presentation at the conference focused on in-the-trenches deep learning, and was titled "Deep Learning: Modular in theory, inflexible in practice." In the interview, Diogo and I discuss the ideas he presented, which are centered on the data, software, optimization and understanding issues surrounding deep learning. Diogo is also a past 1st place Kaggle competition winner, and we also spend some time discussing the competition he competed in and the approach he took lisinopril 10 mg tablet. A bit of a listener warning: Our conversation gets pretty technical pretty quickly. I try to make sure to summarize key points from time to time, and if you hang in there I'm sure you'll learn a lot. Let me know how you like this level of detail. Also, as is the case with my other field recordings, there's a bit of unavoidable background noise. Sorry for that.